Knowledge Representation for Image Feature Extraction

Knowledge Representation for Image Feature Extraction

Author		: Nyoman Karna; Iping Suwardi; Nur Maulidevi
Published on	: International Conference on Soft Computing, Intelligent System and Information Technology (Bali Dynasty Resort, Kuta, Bali)

Abstract

In computer vision, the feature(s) of an image can be extracted as information using deep learning approach. This type of information can be used for further processing, for example to establish a visual semantic, which is a sentence that gives a description about the image. Usually this type of information is stored in a database point of view, which explains the relation between image feature and image description. This research proposes knowledge representation point of view to store the information gathered from image feature extraction, which in return, some new benefits can be obtained by using this approach. Two benefits that can be delivered by using knowledge representation instead of database point of view are integration capability with another source of information from related knowledge-based system and possibility to produce a high-level specific knowledge.